Robust optimization model for remanufacturing system in uncertain reverse logistics environment

The remanufacturing process of reusable parts in uncertain reverse logistics environment is considered. An existing framework for remanufacturing system is adopted. In this framework, the manufacturer has two alternatives for supplying parts: either ordering the required parts to external suppliers or overhauling returned products and bringing them back to dasiaas newpsila conditions. The numbers of returned products are uncertain and can be described as a scenario set with certain probability. By using the approach of robust optimization based on scenario analysis, a robust optimization model is constructed to maximize the total cost savings by optimally deciding the quantity of parts to be processed at each remanufacturing facilities, the number of purchased parts from subcontractor. The results of a numerical example show that the model we proposed is both solution-robust and model-robust.